Document content analysis technology for reducing cognitive load

ABSTRACT

The present invention provides for analyzing document content for display with reduced cognitive load assists those who are blind, have low vision, or cognitive problems. This present invention also aids those who prefer to receive condensed information orally. Document content is analyzed, a set of salient words and phrases are generated from the document content and the set of salient words and phrases are read.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims the benefit of thefiling date of, co-pending U.S. patent application Ser. No. 10/932,725entitled DOCUMENT CONTENT ANALYSIS TECHNOLOGY FOR REDUCING COGNITIVELOAD filed Sep. 2, 2004.

FIELD OF THE INVENTION

The present invention relates generally to accessibility functions for adocument on a computer and, more particularly, to a method for analyzingdocument content that reduces the cognitive load for a user.

BACKGROUND

When reading newspapers, documents, or web pages, there are significantamounts of text in which salient information is imbedded. For peoplewith low vision, dyslexia, blindness, some eye-motor disabilities, andmost cognitive deficiencies, text density and organization createchallenges. Not only is there a huge cognitive processing demandrequired, but the individual must parse meaningful information fromnon-meaningful information without the benefit of additional cueing(e.g., color, chunking, etc). In addition, the blind person using ascreen reading device must perform this higher level cognitive functionwhile also listening to the information, making it necessary to retainlarge quantities of spoken information in working memory buffers toderive the meaning contained within a few key words.

Typical industry solutions to date utilize a document summarizer.Summarization technology addresses the problem of information overloadby reducing a full document to a surrogate summary consisting of a fewsentences extracted from the document in a way which retains the essenceof the document content. Summarization technology addresses technicalchallenges like coherence, cohesion, and information quotient. However,even though the information reduction it achieves would help a personwith cognitive disabilities, summarization does not explicitly addressperceptual problems which might require solutions identifying salienttext fragments of granularity smaller than a sentence.

In particular, none of the summarization technologies listed above ‘tag’words or phrases with a salience measure. Consequently, thesetechnologies are unable to focus on short text fragments; brevity beingof the essence from the point of view of a person with cognitivedisabilities. Furthermore, not much attention has been paid tocontextualizing the salient fragments. Summarization solutions do not,typically, relate a summary to the original document source, which makesit hard to create a cognitive map between the summary and the full text.

Therefore, there is a need for a solution to reduce the heavy cognitiveload, addressing at least some of the problems associated withconventional document summarizers.

SUMMARY OF THE INVENTION

The present invention provides for Document content analyzing documentcontent so the content can be displayed with reduced cognitive load. Thedocument content is analyzed and a set of salient words and phrases aregenerated from the document content. A marked-up document containing theset of salient words and phrases are then read.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention, and theadvantages thereof, reference is now made to the following DetailedDescription taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 illustrates a method for analyzing document content anddisplaying the document content with a reduced cognitive load;

FIG. 2 illustrates a detailed method of analyzing document content;

FIG. 3 illustrates a method of generating a set of salient words andphrases; and

FIG. 4 illustrates a method of reading a salient marked-up documentincluding the salient words and phrases of the salient marked-updocument.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is described to a large extent in thisspecification in terms of methods and systems for analyzing documentcontent for display with a reduced cognitive load. However, personsskilled in the art will recognize that a system for operating inaccordance with the disclosed methods also falls within the scope of thepresent invention. The system could be carried out by a computer programor parts of different computer programs.

This invention can also be embodied in a computer program product, suchas a CD-Rom or other recording medium, for use with any suitable dataprocessing system. Persons skilled in the art would recognize that anycomputer system having suitable programming means will be capable ofexecuting the steps of the method of the invention as embodied in aprogram product. Although most of the exemplary embodiments described inthis specification are oriented to software installed and executing oncomputer hardware, persons skilled in the art would recognizealternative embodiments implemented as firmware or as hardware arewithin the scope of the present invention.

Referring now to FIG. 1, the reference numeral 100 generally indicates asystem by which document content can be received. A remote computer 154or a server 152 connected by a network 111 sends document content 190 toa local computer 150. Also, a local computer can already have access tothe document content 190 through internal storage such as a hard driveor RAM, or other stored data such as a CD-Rom.

A “Network” is used in this detailed description to mean one of anynetworked pairing for data communications among computers or computersystems. Examples of networks include intranets, extranets, internets,local area networks (LAN), wide area networks (WAN), and other networkarrangements as would occur to those persons of skill in the art.

Referring now to FIG. 2 the reference numeral 200 generally indicates anexemplary system for document content analysis. In the system 200,document content 190 is sent to a document content analyzer 192. Afterthe document content 190 is analyzed by the document content analyzer192, a salient word generator 194 creates a set of salient words andphrases 196 from the document content 190. The set of salient words andphrases 196 can also be included as part of a larger, salient marked-updocument. Although not depicted in the exemplary system 200, a salientword generator can also be included as part of a document contentanalyzer as would occur to those of skill in the art. A reader 198capable of reading the set of salient words and phrases 196 can createaudible representations by sending the set of salient words and phrases196 to a text-to-speech engine or display the set of salient words andphrases 196 on a computer screen. The reader 198 not only reads the setof salient words and phrases, but can also read XML tags, HTML, imagetags, metatags and so on.

The salient marked-up document not only includes the set of salientwords and phrases but can also include images, tables, charts, and etc.The function of the reader 198 reading images can be suppressed by thesystem 200, or the ALT tags on the images can be read aloud. Forexample, words in that salient marked-up document underlined by thedocument content analyzer could be read louder, or HTML links could beread in a different voice. The method of FIG. 1 can read tables, forms,and frames and allows users to search for specific text on a Web page aswell as on the entire Web.

Salient, as used in this specification, means prominent and alsoincludes having a quality that thrusts itself into attention. Salienceacts as a mediator for the type and quantity of the informationreduction over the original document, defined in terms of small, brief,information-bearing chunks. Salient words and phrases are the words andphrases considered by the document content analysis as bearinginformation.

Document content analysis, in a particular configuration, aims toprocess a text document, and by means of a pipeline of linguisticprocessing (interchangeably driven by morphosyntactic rules and/orstatistical models of human language subsystems), it identifies wordsand phrases which are potential ‘bearers’ of new information. Amorphosyntactic operation is an ordered, dynamic relation between onelinguistic form and another.

Turning now to FIG. 3, the reference numeral 300 generally indicates anexemplary method for analyzing document content. The method 300 includesselecting a threshold of prominence 352. Selecting a threshold ofprominence 352 is typically carried out by a user at a computer usingcomputer inputs such as a mouse or a keyboard. Alternatively, the method300 includes using the default prominence 354 settings. Selecting athreshold of prominence includes selecting prominence settings such asthose for identifying, word, sentence, and paragraph boundaries.

Document content found to fall below the threshold level of prominencedoes not have to be literally dropped. The document content that fallsbelow the threshold of prominence can remain in the document and remainunmarked or can be deleted from the document completely.

After either selecting the threshold of prominence 352 or using thedefault prominence settings 354, the exemplary method 300 includesidentifying salient words and phrases 356. Identifying salient words andphrases can be carried out by counting names, or by recognizing domainterms, abbreviations and document tags. Identifying salient words andphrases 356 works best with documents in which the major documentstructure elements are explicitly indicated. Structural elements includebut are not limited to titles, headings, headers, footers, tables,lists. Identifying salient words and phrases can also be typicallycarried out by scanning the text for words and phrases that rise abovethe selected threshold of prominence. The document structural cues areinformative of which sentences are salient by virtue of their positionand which portions of text should not be considered. For documentswithout structural cues, the method 300 can also rely on general wordstatistics, such as word counts, to determine salience.

The method 300 also includes contextualizing salient words and phrases358. After identifying the salient words and phrases 356, the method 300contextualizes salient words and phrases to discover whether or not theidentified salient words and phrases make sense. Typically, most wordprocessors contain spell checkers that contextualize salient words andphrases and can be modified by those with skill in the art to carry outcontextualizing salient words and phrases in the method 300.Contextualizing the salient words and phrases 356 also typicallyinvolves arranging the identified salient words and phrases and placingthem in a certain context. The method 300 determines which order andsense the set of salient words and phrases belong. After contextualizingthe salient words and phrases, the method 300 generates the salientwords and phrases.

Generating the salient words and phrases includes tagging the salientwords and phrases. Salient words and phrases are tagged before creatingthe salient marked-up document. Tagging the salient words and phrases istypically done by a form of markup. Markup can be HTML language,highlighting, bold letters, etc., as long as the markup indicates thesalient words and phrases of the original document to create a set ofsalient words and phrases in which the content-bearing items were found.Alternatively, generating the salient words and phrases can also includeerasing text determined to be below the level of salience from thedocument. This is then used by the text markup means to mark up the textaccordingly. The salient text can also be highlighted, or marked up insome other way to represent the higher level of prominence.

Referring now to FIG. 4 the reference numeral 400 generally indicates asystem for reading the set of salient words and phrases. Once the set ofsalient words and phrases 196 has been generated, the set of words andphrases can be sent to a reader 198 individually or as part of a salientmarked-up document 402. In the system 400, the reader 198 includes anaudible representations generator 404 capable of producing soundsrepresenting the set of salient words and phrases 196 thru a computer150 to speakers 406. Typical embodiments of an audible representationsgenerator include any text-to-speech converter, such as IBM'stext-to-speech engines or Home Page Reader.

The Home Page Reader is an accessibility product, such as an IBMaccessibility product, designed to allow people who are blind or havelow vision to “read” the web. It utilizes Web Access Technology (WAT) asits engine to navigate an HTML Document Object Model (DOM), such as theInternet Explorer (IE) DOM. WAT generates data packets containingtextual content and information about each web page element, which isrepresented by one or more DOM nodes. A user interface (UI) component,such as the Home Page Reader browser or a document reader, sendsrequests for specific types of data packets to WAT based on keyboard,mouse, or document events, such as the loading of a web page or the Tabkey being pressed. Upon receiving a data packet from WAT, the UIcomponent extracts the text content and information from the packet togenerate both text and speech views of the web page. The text view candistinguish different types of elements, such as key words or phrases,using visual text characteristics such as font size, type, color, andstyle. The speech view uses different speech characteristics, such asspeech rate, different voices, sounds files, and leading or trailingtext, to differentiate different types or elements on the web page. Togenerate speech output, the Home Page Reader incorporates an abilitythat is capable of converting text to audible sounds.

The Home Page Reader can read the text aloud. The way the text is readwill vary based on the markups. Images can be suppressed, or the ALTtags on the images could be read aloud. For example, words underlined bythe document content analyzer could be read louder, or HTML links couldbe read in a different voice. Home Page Reader reads the full range ofthe Web page data in a logical, clear and understandable manner. Itreads tables, forms, and frames and allows users to search for specifictext on a Web page as well as on the entire Web. In addition, Home PageReader reads HTML 4.0 information provided by Web page authors, givinginformation such as table summaries and captions. Home Page Reader readsthe full range of the Web page data in a logical, clear andunderstandable manner.

Not limited to the Home Page Reader, any compatible text-to-speechconverter can also be used in the method of analyzing document contentfor display with reduced cognitive load. To be compatible, atext-to-speech converter must be able to recognize the differences inthe text of the marked up document. The method described herein can beembedded in a software product, in which case the software product canmark up the text, and then send it over the internet to a client runninga program capable of the Home Page Reader function.

It is understood that the present invention can take many forms andembodiments. Accordingly, several variations can be made in theforegoing without departing from the spirit or the scope of theinvention. The capabilities outlined herein allow for the possibility ofa variety of programming models. This disclosure should not be read aspreferring any particular programming model, but is instead directed tothe underlying mechanisms on which these programming models can bebuilt.

Having thus described the present invention by reference to certain ofits preferred embodiments, it is noted that the embodiments disclosedare illustrative rather than limiting in nature and that a wide range ofvariations, modifications, changes, and substitutions are contemplatedin the foregoing disclosure and, in some instances, some features of thepresent invention can be employed without a corresponding use of theother features. Many such variations and modifications can be considereddesirable by those skilled in the art based upon a review of theforegoing description of preferred embodiments. Accordingly, it isappropriate that the appended claims be construed broadly and in amanner consistent with the scope of the invention.

1. A computer implemented system for analyzing document content fordisplay with reduced cognitive load, comprising: means for receiving adocument for analysis; means for analyzing document content of thedocument; means for generating a set of salient words and phrases fromthe document content based upon the linguistic content of the words andphrases in the document; means for tagging the salient words and phrasesin the set of salient words and phrases; and means for reading the setof salient words and phrases.
 2. The system of claim 1 furthercomprising means for receiving document content over a network.
 3. Thesystem of claim 1 further comprising means for selecting a threshold ofprominence for the salient words and phrases.
 4. The system of claim 1wherein means for analyzing document content further comprises meansidentifying salient words and phrases of the document content.
 5. Thesystem of claim 4 further comprising means for contextualizing thesalient words and phrases.
 6. The system of claim 1 wherein said meansfor reading the document content further comprises means for reading thesalient words and phrases.
 7. The system of claim 6 wherein said meansfor reading the salient words and phrases further comprises means forgenerating audible representations of the salient words and phrases. 8.The system of claim 6 wherein said means for reading the salient wordsand phrases is a Home Page Reader means.
 9. A computer program productfor analyzing document content for display with reduced cognitive load,the computer program product having a tangible computer-readable mediumwith a computer program embodied thereon, the computer program executedon a computer comprising: computer code for receiving a document foranalysis; computer code for analyzing document content of the document;computer code for generating a set of salient words and phrases from thedocument content based upon the linguistic content of the words andphrases in the document; computer code for tagging the salient words andphrases in the set of salient words and phrases; and computer code forreading the set of salient words and phrases.
 10. The computer programproduct of claim 9, further comprising computer program code forselecting a threshold of prominence for the salient words and phrases.11. The computer program product of claim 9, further comprising computerprogram code for contextualizing the salient words and phrases.
 12. Thecomputer program product of claim 9 wherein the computer code forreading the set of salient words and phrases further comprises computercode for utilizing a Home Page Reader.